Multiple extracellular electrodes can be used in concert to record the activity of a neural population, elucidating the complex process by which neurons code, process, learn, and retain information. Because evidence suggests that information coding involves coordinated activity of groups of neurons, such simultaneous recordings of whole neural populations are necessary for understanding coding. However, in the complex data records that result, individual neural signals are often difficult to distinguish. As a result, most researchers who collect multielectrode data must also develop their own data-processing software to determine the time-of-occurrence of action potentials, or "spikes" from the recorded neural population, a process known as "spike-sorting." The objective of this project is to develop MATLAB software toolbox for multichannel, multielectrode spike sorting that consolidates a variety of spike-sorting solutions and that incorporates state-of-the-art algorithms using advanced signal processing techniques. This will be the first commercial software package to offer effective solutions to two major spike-sorting difficulties: discrimination and identification of spike superpositions, and quantification of spike-sorting accuracy. In addition, the product will be open-source to allow users to easily add or modify modules and promote algorithm comparisons and sharing between investigators.